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gpower-mcp

gpower-mcp

by abdulkadirelaldi
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Python
Remote

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct role: discovery, single-test description, single power analysis, power curve tabulation, effect-size conversion, and provenance reporting. The only near-overlap is between power_analysis and power_curve, but their descriptions make the single-result versus tabulated trade-off explicit.

    Naming Consistency4/5

    All names use snake_case consistently, and most are readable verb-led or domain-specific names. However, the set mixes verb_noun names like list_tests and compute_effect_size with noun phrases like power_curve and engine_provenance, so it is not a strict uniform pattern.

    Tool Count5/5

    Six tools is well within the ideal range for a focused statistical power engine. Each tool covers a distinct part of the workflow, and none feels redundant or padded.

    Completeness5/5

    The surface covers test discovery, detailed test metadata, power analysis across all solve-for modes, power curves, effect-size conversion, and provenance. For a G*Power-style engine, this is a complete lifecycle with no obvious dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing

    Resources